Understanding Analytic Workloads – Learn When to Turn the Tables on Your Big Data
Jim Tommaney
"Big Data analytics" is a widely over-subscribed term, used by vendors with wildly different architectures to describe their technology.  Matching the right tools for your analytic workloads can take the difficulty out of Big Data analytics and deliver easy data analytics.
Analytic Workloads vary based on some critical dimensions:
  • Type of Analysis: Does the analysis focus on records that describe single entities, or finding patterns between and within records?
  • Flexibility of Analysis: What are the flexibility/extensibility requirements? Do you have a handful of analysis patterns that are fixed, or are the patterns diverse, dynamic, and growing?
  • Schema: Reliance on schema on demand or pre-defined schema, or both? 
  • Scope of Analysis: Related to size of data.  How many records are referenced in support of some analytics operation?
Pure columnar storage combined with linear scalability when distributing work can deliver game-changing performance for Analytic Workloads. Learn where different Big Data technologies (including columnar) best fit to solve specific workload challenges in today’s Big Data landscape.

This class is sponsored by Calpont.

Level : Intermediate